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External reviews

23 reviews
from G2

External reviews are not included in the AWS star rating for the product.


    Marc S.

Excellent framework and application

  • January 19, 2021
  • Review verified by G2

What do you like best?
Excellent support for commercial product Driverless AI. Rapid iteration. Performance is generally better than one can be achieved in code.
What do you dislike?
Actually nothing. The combination of proprietary and open source tools, Driverless AI and H2O, provide tools across a full range of use cases.
What problems are you solving with the product? What benefits have you realized?
We work in both financial services and biological research.
Recommendations to others considering the product:
Take advantage of the 30 day trial.


    Renzo S.

Workflows for quick ML prototyping

  • November 16, 2020
  • Review provided by G2

What do you like best?
They developed top-quality open source tools, including the H2O-3 and AutoML families. I do not have a license for their Driverless AI, but my experience with it through tutorials and other demos has been superb. I should mention that their efforts to develop frameworks for ML interpretability are spot on, and their learning center is shaping up as a valuable resource to the community in general. The interfaces with R and Python enable a smooth transition of pre-existing workflows into the H2O framework.
What do you dislike?
Somewhat cryptic debugging msgs in H2O-3. They support specific packages for manipulating data (data.table in R, datataable in Python) for the sake of speed and big data maneuverability, although many users may find this limiting. Driverless AI may not be affordable to the small fish in the pond.
What problems are you solving with the product? What benefits have you realized?
I have mostly used their AutoML to build quick ML/AI prototype solutions in different domains.
Recommendations to others considering the product:
One should leverage all the resources available to test their products before buying.


    Jiook C.

h2o is my personal data scientist

  • November 13, 2020
  • Review provided by G2

What do you like best?
h2o offers a well validated, fully automated, rigorous machine learning pipeline including state of the art model interpretation allowing for prediction and inferences.
What do you dislike?
i have nothing dislike about h2o's products.
What problems are you solving with the product? What benefits have you realized?
my scientific questions involve biomedicine, neuroscience, and psychology


    Binesh S.

Great Machine Learning Framework

  • September 23, 2020
  • Review provided by G2

What do you like best?
The ability to try out multiple models with a few lines of the code is the greatest benefit
What do you dislike?
H20 does a good job in abstraction of underlying transformation and tuning steps, which could be a bit challenging
What problems are you solving with the product? What benefits have you realized?
1. Policy Lapse Predictor - the biggest benefit is the automation of model tuning
Recommendations to others considering the product:
Great framework


    Research

Accessible ML

  • September 22, 2020
  • Review provided by G2

What do you like best?
Clean interface through Driverless AI and variety of analyses
What do you dislike?
Better instructions would be helpful, as would clearer tutorials
What problems are you solving with the product? What benefits have you realized?
Need for adaptable ML analyses. Plug and play.


    Banking

Its superb

  • August 06, 2020
  • Review provided by G2

What do you like best?
Ease of use and its high performance for building models
What do you dislike?
Does not support data cleaning and some algorithms
What problems are you solving with the product? What benefits have you realized?
Used to solve complex machine learning problems


    Non-Profit Organization Management

Great ML framework

  • July 24, 2020
  • Review provided by G2

What do you like best?
This is a cross-platform, integrated framework for ML that is continuing to evolve with topics important to data scientists.
What do you dislike?
Developing support for a wide range of NLP preprocessing
What problems are you solving with the product? What benefits have you realized?
Problems in academic research and healthcare


    Capital Markets

Great Product

  • July 24, 2020
  • Review verified by G2

What do you like best?
The best part of H2O.ai is its ease of use and seamless UI.
What do you dislike?
One downside of H2O.ai is, as with many services, its bugs which do not return human-readable debugging statements.
What problems are you solving with the product? What benefits have you realized?
I have used H2O for time-series data, and stock market prediction.


    Rafael P.

A very good experience with Machine Learning

  • July 13, 2020
  • Review verified by G2

What do you like best?
AutoML is a great product. They have other ones, but AutoML is the most impressive.
What do you dislike?
Nothing, maybe the integration with Spark could be improved but only in little details.
What problems are you solving with the product? What benefits have you realized?
Forecasting models and finding for best algorithms for my datasets
Recommendations to others considering the product:
It's an amazing set of tools, easing the use of machine learning and giving a lot of advances to write & discover models.


    Electrical/Electronic Manufacturing

Driverless AI application for Auomated Machine Learning and Data Analytics

  • July 07, 2020
  • Review provided by G2

What do you like best?
Easy to use with good UI design and automated ML function. Driverless AI has strong capability on the auto feature engineering and system visualization. The auto feature engineering has supported different machine learning algorithm (Random Forest, Decision Tree, Neural Network, Deep Learning, etc.) and feature parameter tuning (accuracy, time, system computing etc.) The system also helps user to reduce time and efforts for hyparemeter tuning and compare the model with different settings. This will optimize the process and provide the most efficient model for prediction in classification or regression domain. Besides, Driverless AI also has good UI design and visualization. The UI also supports end user to quickly import data, visualize data in different categories, as well as check on the system running and performance during the Auto ML process. The end user could also observe experiment summary and accuracy matrix, as well as model comparison in term of accuracy.
In addition, Driverless AI also supports the AI Interpretation to explain on the model and performance. This function is very helpful to end user for understanding the Machine Learning blackbox, as well as management team for decision making based on extensive information.
What do you dislike?
It is great if Driverless AI could support deployment for edge computing, which is common in IoT world. The edge computing will require efficient computing and good accuracy with AutoML algorithm. This will help much the customer for deployment.
What problems are you solving with the product? What benefits have you realized?
Data analytics for predictive maintenance. It could make easy-to-use for system operator.
Recommendations to others considering the product:
Yes, H2O.ai DriverlessAI is a good AutoML platform for company, which does not have Data Scientist.